Features of the tasks of identifying and observing groups of unmanned letter vehicles

IF 0.2 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC Visnyk NTUU KPI Seriia-Radiotekhnika Radioaparatobuduvannia Pub Date : 2022-12-30 DOI:10.30837/rt.2022.4.211.06
V. Kartashov, V.A. Pososhenko, A. Kapusta, M. Rybnykov, E.V. Pershin
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Abstract

The current trend towards increasing the efficiency of UAV use is the transition from their single use to group use. In accordance with this, when building a complex integrated system for detecting and monitoring UAVs, including various information channels, it is advisable to take into account the features of the system functioning associated with the detection of groups of UAVs. The article discusses the information, energy and search capabilities of individual detection tools being a part of the integrated UAV surveillance system in order to build an effective algorithm for joint processing of incoming input signals, taking into account various capabilities of individual channels (in terms of range, recognition, etc.). An optimal algorithm for detecting groups of UAVs in a complex integrated system combining detection decisions made in private channels is synthesized. According to the synthesized algorithm, complex processing consists in summing up the solutions of individual detectors with some weights determined by the quality of the decisions made in the channels. The quality of solutions, in turn, depends on the technical means used in the channels and the conditions of observation. A sequence for solving a set of interrelated tasks in a complex integrated UAV surveillance system as the group target approaches the protected object is proposed. The sequence includes the following operations: identification of a group target (energy detection); estimation of coordinates of a group of objects; spatial resolution and determination of the number of vehicles in a group; recognition (type determination) of each individual device; assessment of the coordinates of each aircraft separately; determination of the composition of the group (homogeneous, heterogeneous); determination of the specialization of the group and revealing the nature of its tasks.
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无人信车群识别与观测任务特征
当前提高无人机使用效率的趋势是由单一使用向成组使用转变。因此,在构建包含多种信息通道的复杂的无人机检测与监控综合系统时,应考虑到与无人机群检测相关的系统功能特点。本文讨论了作为无人机综合监视系统一部分的单个检测工具的信息、能量和搜索能力,以便在考虑单个通道的各种能力(在距离、识别等方面)的情况下,建立一个有效的算法来联合处理输入信号。综合了一种结合专用信道检测决策的复杂集成系统中无人机群检测的优化算法。根据综合算法,复杂处理包括将单个检测器的解与通道中决策质量决定的一些权重相加。解决方案的质量反过来又取决于通道中使用的技术手段和观察条件。提出了一种复杂集成无人机监视系统中,当群目标接近保护对象时,求解一组相互关联任务的序列。所述序列包括以下操作:识别一组目标(能量检测);一组目标的坐标估计;空间分辨率和一组车辆数量的确定;单个设备的识别(类型确定);分别评估每架飞机的坐标;组份组成的确定(同质、异质);确定小组的专业化并揭示其任务的性质。
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Visnyk NTUU KPI Seriia-Radiotekhnika Radioaparatobuduvannia
Visnyk NTUU KPI Seriia-Radiotekhnika Radioaparatobuduvannia ENGINEERING, ELECTRICAL & ELECTRONIC-
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